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https://api.github.com/repos/huggingface/transformers/issues/8
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8
fixed small typos in the README.md
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[ "Many thanks!" ]
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Develop
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Fixing `run_squad.py` pre-processing bug. Various clean-ups: - the weight initialization was not optimal (tf. truncated_normal_initializer(stddev=0.02) was translated in weight.data.normal_(0.02) instead of weight.data.normal_(mean=0.0, std=0.02) which likely affected the performance of run_classifer.py also. - ...
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6
Failure during pytest (and solution for python3)
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[ "Thanks, I update the readme." ]
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``` foo@bar:~/foo/bar/pytorch-pretrained-BERT$ pytest -sv ./tests/ ===================================================================================================================== test session starts =================================================================================================================...
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MRPC hyperparameters question
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[ "Hi Ethan,\r\nThanks we used the MRPC hyper-parameters indeed, I corrected the README.\r\nRegarding the dev set accuracy, I am not really surprised there is a slightly lower accuracy with the PyTorch version (even though the variance is high so it's hard to get something significant). That is something that is gene...
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When describing how you reproduced the MRPC results, you say: "Our test ran on a few seeds with the original implementation hyper-parameters gave evaluation results between 82 and 87." and you link to the SQuAD hyperparameters (https://github.com/google-research/bert#squad). Is the link a mistake? Or did you use t...
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Fix typo in subheader BertForQuestionAnswering
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[ "exact thanks !" ]
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CONTRIBUTOR
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Should say `BertForQuestionAnswering`, but says `BertForSequenceClassification`.
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run_squad questions
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[ "It also seems to me that the SQuAD 1.1 can not reproduce the google tensorflow version performance.", "> It also seems to me that the SQuAD 1.1 can not reproduce the google tensorflow version performance.\r\n\r\nWhat batch size are you running?", "I'm running on 4 GPU with a batch size of 48, the result is {\"...
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Thanks a lot for the port! I have some minor questions, for the run_squad file, I see two options for accumulating gradients, accumulate_gradients and gradient_accumulation_steps but it seems to me that it can be combined into one. The other one is for the global_step variable, seems we are only counting but not using ...
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Port tokenization for the multilingual model
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[ "Thanks for that, sorry for the delay" ]
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Create DataParallel model if several GPUs
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